Tracking system and method for tracking wood products in a production line

ABSTRACT

The wood tracking system for a production line generally has a wood product optimizer; a wood product trimmer downstream from the optimizer in the production line; a conveyor for moving wood products from the optimizer to the trimmer and across a handling area therebetween, the optimizer being configured to scan each of the wood products in a given order and to generate optimization data for each wood product; and a computer vision system positioned proximate the handling area along the production line, the computer vision system having a camera, a processor in communication with the optimizer and with the trimmer and a computer-readable memory for storing the optimization data, the processor being configured to acquire images of the handling area from the camera, the processor being configured to associate the optimization data of a given wood product across each of the images until it arrives at the trimmer.

FIELD

The improvements generally relate to a wood product production lineincluding an optimizer and a trimmer, and more particularly relates to atracking system which helps tracking each wood product from theoptimizer to the trimmer.

BACKGROUND

In the wood product industry, prices can vary on a daily basis.Accordingly, it is of importance for a wood product producer to optimizeits production based on the current prices. More specifically, thepricing of the wood product can vary depending of its dimensions (e.g.length) and quality. Although greater length of wood products istypically associated with greater pricing, the presence of a defectalong a length of the wood product can negatively affect the qualitylevel of the product as a whole. Accordingly, in some instances, it ispreferable to trim the defect off in a manner to obtain a shorter woodproduct of a greater quality, for instance.

Considering that, in a typical production line, the wood products aremoved at a speed that can range between 366 m/min (1200 ft./min) and 610m/min (2000 ft./min), these decisions have to be taken in an automatedmanner.

Accordingly, an example of a production line can include one or moreconveyors for moving, for instance, wood products from a wood productoptimizer to a wood product trimmer (simply referred to as “theoptimizer” and “the trimmer”). The optimizer is generally configured toscan successive ones of the wood products, to decide whether or not andhow to trim each wood product based on the current prices and togenerate optimization data that the trimmer can use as cuttinginstructions on how to trim the wood product.

To ensure that given optimization data be used for a corresponding woodproduct, the typical production line generally includes a wood tracker.An example of such a wood tracker is provided in Canadian PatentApplication No. 2 245 412 A1. For instance, this wood tracker applies aninformation mark pattern indicative of the optimization data on eachwood product following scanning by the optimizer using upper and lowerpairs of luminescent ink-jet devices. Prior to arriving to the trimmer,the wood tracker uses optical sensing devices each having luminescenceinducing light source to read the information mark pattern and generatesan output signal based on the reading of the optical sensing devices.The output signal is then used by the trimmer as cutting instructions totrim the wood product in accordance with its optimization data.

Although existing wood trackers were satisfactory to a certain degree,there always remains room for improvement.

SUMMARY

For instance, there is a specific need in avoiding the use of ink-jetdevices, and any other marking device, in such a production line. Forinstance, maintenance of these marking devices has been found to becostly in terms of productivity because any time one of the markingdevices breaks, the production line has to be stopped for a given periodof time. In another example, the information mark pattern marked on awood product happens to be applied onto a defect of the wood productwhich may later prevent readability of the information mark pattern. Forat least these reasons, existing wood trackers have been foundconsiderably impairing the productivity of the production line.

There is provided a wood tracking system using computer vision which canavoid the aforementioned drawbacks of the existing wood producttrackers. By analyzing successive images of a handling area, each woodproduct can be tracked from the optimizer to the trimmer without markingdirectly on the wood product.

It is thus contemplated that an aim of the wood tracking system is toreduce costs associated to existing wood trackers (e.g., costs ofluminescent ink, costs of ink-jet device parts, costs of the maintenancethereof, costs associated to the presence of unidentifiable wood productalong the production line).

In accordance with another aspect, there is provided a wood trackingsystem for a production line, the wood tracking system comprising: awood product optimizer positioned along a production line; a woodproduct trimmer positioned downstream from the wood product optimizer inthe production line; a conveyor configured for moving a plurality ofwood products from the wood product optimizer to the wood producttrimmer and across a handling area between the wood product optimizerand the wood product trimmer, the wood product optimizer beingconfigured to scan each of the wood products in a given order and togenerate optimization data for each wood product; and a computer visionsystem positioned proximate the handling area along the production line,the computer vision system having a camera, a processor in communicationwith the wood product optimizer and with the wood product trimmer and acomputer-readable memory for storing the optimization data, theprocessor being configured to acquire at least two images from thecamera and representing the handling area at at least two differentmoments in time, the processor being configured to associate theoptimization data of a given wood product represented in a first one ofthe at least two images to a corresponding wood product represented in asecond one of the at least two images until the given wood productarrives at the trimmer.

In accordance with another aspect, there is provided a method oftracking wood products being transversely moved across a handling areaof a production line at a transverse speed, the method comprising:obtaining position and orientation data and optimization data associatedto each wood product of a first sample present in the handling area at afirst moment in time; using a processor, anticipating position andorientation data of each wood product of the first sample at a secondmoment in time assuming an incremental transverse movement based on thetransverse speed and on the position and orientation data associated toeach wood product of the first sample; acquiring, from a camera, animage representing each wood product of a second sample present in atleast the handling area at the second moment in time and analyzing theimage to determine actual position and orientation data associated toeach wood product of the second sample; and tracking each wood productfrom the first sample to the second sample by associating theoptimization data of each wood product of the first sample to arespective wood product of the second sample based on the anticipatedand actual position and orientation data.

In accordance with another aspect, there is provided a method wherein astep of obtaining position and orientation data associated to one ormore wood products includes acquiring, from the camera, an imagerepresenting each wood product present in the handling area at a givenmoment in time; and analyzing the image to determine the position andorientation data associated to each wood product present in the handlingarea at the given moment in time.

Many further features and combinations thereof concerning the presentimprovements will appear to those skilled in the art following a readingof the instant disclosure.

DESCRIPTION OF THE FIGURES

In the figures,

FIG. 1 is a schematic view of an example of a production line for woodproducts;

FIG. 2 is a flowchart of an example of a method of tracking woodproducts being transversely moved across a handling area of theproduction line of FIG. 1;

FIG. 3 is an oblique view of a portion of the handling area of theproduction line of FIG. 1 at a first moment in time whereas FIG. 3A is afirst image representing a portion of the handling area of FIG. 3;

FIG. 4 is an oblique view of a portion of the handling area of theproduction line of FIG. 1 at a second moment in time whereas FIG. 4A isa second image representing a portion of the handling area of FIG. 4;and

FIG. 5 is an oblique view of a portion of the handling area of theproduction line of FIG. 1 at a third moment in time whereas FIG. 5A is athird image representing a portion of the handling area of FIG. 5.

DETAILED DESCRIPTION

FIG. 1 shows an example of a wood tracking system 10 of a productionline 11 for elongated wood products 12 such as lumbers, logs and thelike (simply referred to as “wood products 12”).

As depicted, the wood tracking system 10 includes an optimizer 14, acomputer vision system 16 and a trimmer 18. An optional wood productloader 17 may be provided upstream from the trimmer 18 and proximatethereto to load each wood product into the trimmer 18.

In this example, the movement of the wood products 12 is allowed by twoseparate conveyors, one being a longitudinal conveyor 20 and the otherbeing a transverse conveyor 22. It is understood that in otherembodiments, the number, type and arrangement of conveyor(s) may differ.

For instance, the longitudinal conveyor 20 is used to move the woodproducts 12 along a longitudinal path 24 and across an optimization areaproximate to the optimizer 14. The transverse conveyor 22 is used tomove the wood products 12 from an end 24 a of the longitudinal path 24,along a transverse path 26 at a transverse speed, across a handling area28 of the production line and towards a downstream cutting areaproximate to the trimmer. Handling of the wood products for manual andvisual inspection may be limited to the handling area 28.

Since longitudinal speeds involved in such a production line 11 arerelatively fast (e.g., between 366 m/min and 610 m/min), a stopper 32can be provided proximate to the end 24 a of the longitudinal path 24 tostop each wood product 12 as they are “thrown” by the longitudinalconveyor 20 towards the stopper 32.

The optimizer 14 is configured to scan successive ones of the woodproducts 12 and to generate optimization data 34 for each wood product12. In this example, the optimization data 34 are sequentiallytransmitted to the trimmer 18 in a particular order such that a queue ofoptimization data arrives at the trimmer 18 during use. The optimizationdata can include identification data indicating an order number of agiven wood product in the queue, a type of the given wood product, agrade of the given wood product, a price, etc.

It is thus understood that any reordering of the wood products 12between the optimizer 14 and the trimmer 18 may lead to a wood productbeing trimmed using the optimization data of another wood product andcause inefficiencies in the production line 11. For instance, some woodproducts may be reordered from their given order following unexpectedbouncing onto the stopper 32. Some other wood products may be reorderedby handling of the wood products in the handling area 28. Other reasonsfor reordering may also apply.

To address potential reordering of the wood product 12, the computervision system 16 of the wood tracking system 10 can be used to trackeach wood product 12 in the handling area 28 such that any reordering ofthe wood product 12 causes reordering of the optimization data in orderfor the trimmer 18 to trim each wood product 12 with their correspondingoptimization data.

More specifically, the computer vision system 16 has a camera 40, aprocessor 42 in communication with the optimizer 14 and with the trimmer18 and a computer-readable memory 44.

More specifically, the camera 40 has a field of view 46 substantiallycorresponding to the handling area 28. The handling area 28 can extendfrom the end 24 a of the longitudinal path 24 of the longitudinalconveyor 20 to an end 26 a of the transverse path 26 of the transverseconveyor 22.

The camera 40 is configured to generate one or more images 48representing the handling area 28 at each of successive moments in timeduring use of the wood tracking system 16. In this embodiment, thecamera 40 has a frame rate of at least 20 fps and has a resolution of atleast 1 megapixel. The frame rate of the camera, as well as its shutterspeed, can be controlled by the processor 42, for instance. It is notedthat depending on the application, the camera 40 can be configured togenerate 2D images and/or 3D images. As it will be understood, in analternate embodiment, the camera 40 includes more than one camera unitsuch that the field of view 46 is composite (i.e. the field of viewresults from the combination of more than one field of view ofcorresponding camera units). For ease of reading, however, the term“camera” is used in its singular form.

As shown in FIG. 1, the processor 42 is connected to the optimizer 14,to the camera 40 and to the trimmer 18 in a wired and/or wirelessfashion. In this embodiment, the processor 42 is configured to receivethe optimization data 34 from the optimizer 14, to acquire the images 48from the camera 40 and to transmit the optimization data 34 to thetrimmer 18 in an order corresponding to the actual order the woodproducts 12 arriving to the trimmer 18. The processor 42 can include oneor more processors but the term “processor” is used in its singular formfor ease of reading. In an alternate embodiment, the processor 42 isremote from the production line 11.

In the example shown in FIG. 1, the processor 42 is in communicationwith the memory 44. The processor 42 and the memory 44 can be part of acomputer (e.g., a personal computer, mobile device, etc.). In thisembodiment, the memory 44 has stored thereon a wood tracking program,which, when run by the processor 42, allows the wood tracking system 16to track the optimization data 34 of each wood product 12 across aplurality of images 48 representing the handling area 28 such that, whena given wood product 12 arrives at the trimmer 18, the processor 42 cantransmit corresponding optimization data 34 for proper cutting.

The instructions of the wood tracking program can be presented in theform of steps of a method that are to be performed by the processor 42.

For instance, FIG. 2 shows an example of a method 100 of tracking woodproducts that are transversely moved across the handling area of theproduction line at a transverse speed.

As shown, the method 100 has a step 102 of obtaining position andorientation data as well as optimization data associated to each woodproduct of a first sample present in the handling area at a first momentin time t1.

Referring now to FIGS. 3 and 3A, each position and orientation data areindicative of a position and of an orientation (θ,d) of a given woodproduct relative to a reference coordinate system (e.g., the referencesystem θ0,d0). Each image of the handling area is calibrated based onthe reference coordinate system to allow comparison between successiveimages.

It will be understood that in such a production line, each wood productis a wood product and can be modeled as being a line having a givenposition relative to a reference point d0 (e.g., the upper left cornerof the image) and extending along a given orientation θ0 relative to areference orientation (e.g., the vertical orientation).

For ease of understanding, reference is now made to FIG. 3 which showsan oblique view of a first sample 60 in a handling area at a firstmoment in time t1 where a first wood product 12 a, a second wood product12 b and a third wood product 12 c are being transversally moved alongthe transverse path 26 by the transverse conveyor 22. FIG. 3A shows anexample of a first image 62 generated by the camera at the first momentin time t1. A direction of transverse movement is shown at arrow A inFIGS. 3 and 3A.

As it will be understood, the position and orientation data can beobtained from the memory where those data have been previously stored.In this embodiment, however, the position and orientation dataassociated to each of the first, second, and third wood products 12 a,12 b, 12 c of the first sample 60 are obtained by analyzing the firstimage 62 acquired from the camera.

As it can be seen, the first image 62 can be analyzed by the processorto determine first position and orientation data indicative of theactual position and the orientation (θ1(t1),d1(t1)) associated to thefirst wood product 12 a at the first moment in time t1, to determinesecond position and orientation data indicative of the actual positionand the orientation (θ2(t1),d2(t1)) associated to the second woodproduct 12 b at the first moment in time t1, and to determine thirdposition and orientation data indicative of the actual position and theorientation (θ3(t1),d3(t1)) associated to the third wood product 12 c atthe first moment in time t1. In this case, first optimization data areassociated to the first wood product 12 a, second optimization data areassociated to the second wood product 12 b and third optimization dataare associated to the third wood product 12 c.

At this stage, referring back to FIG. 2, the method 100 has a step 104of anticipating position and orientation data indicative of the positionand of the orientation (θ′(t2),d′(t2)) of each wood product of the firstsample but at a second moment in time t2 assuming an incrementaltransverse movement Δx based on the transverse speed and on the positionand orientation data associated to the first, second and third woodproduct 12 a, 12 b, 12 c of the first sample 60. The incrementaltransverse movement Δx is assumed to last for an incremental period oftime Δt such that the second moment in time t2 exceeds the first momentin time t1 by the incremental period of time Δt (i.e. t2=t1+Δt).

As will be understood, if no reordering occurs between the first and thesecond moments in time t1 and t2, the anticipated orientation of a woodproduct at the second moment in time t2 can correspond to the actualorientation of the same wood product at the first t1 (i.e.,θ′(t2)=θ(t1)) whereas the anticipated position of a wood product at thesecond moment in time t2 can correspond to the actual position of thesame wood product at the first moment in time t1 plus the incrementaltransverse movement Δx (i.e., d′(t2)=d(t1)+Δx).

For instance, anticipated position and orientation data associated tothe first wood product, the second wood product and the third woodproduct (θ1′(t2),d1′(t2)), (θ2′(t2),d2′(t2)) and (θ3′(t2),d3′(t2)) areshown in the first image 62 of FIG. 3A.

Referring back to FIG. 2, the method 100 has a step 106 of acquiring,from the camera, a second image representing each wood product of asecond sample present in the handling area at the second moment in timet2.

Referring now to FIG. 4, fourth, fifth and sixth wood products 12 d, 12e, 12 f of a second sample 64 are in the handling area at a secondmoment in time t2. The fourth, fifth and sixth wood products 12 d, 12 e,12 f may correspond to a respective one of the first, second and thirdwood products 12 a, 12 b, 12 c, however, the correspondence is notassumed to be known in order to account for potential reordering.

In other words, in this case, the first, second and third wood products12 a, 12 b, 12 c of the first sample 60 can be said to be wood productsidentified in a previous image whereas the fourth, fifth and sixth woodproducts 12 d, 12 e, 12 f of the second sample 64 can be said to be woodproducts identified in a later image. The method described herein helpsassociate each wood product identified in a previous image to a woodproduct identified in a later image.

FIG. 4A shows a second image 66 of the second sample 64. The secondimage 66 can thus be analyzed to determine actual position andorientation data (θ(t2),d(t2)) associated to the fourth, fifth and sixthwood products 12 d, 12 e, 12 f of the second sample 64 at the secondmoment in time t2.

As it can be seen from FIGS. 4 and 4A, the second image 66 can beanalyzed by the processor to determine fourth position and orientationdata indicative of the position and the orientation (θ4(t2),d4(t2))associated to the fourth wood product 12 d at the second moment in timet2, to determine fifth position and orientation data indicative of theposition and the orientation (θ5(t2),d5(t2)) associated to the fifthwood product 12 e at the second moment in time t2, and to determinesixth position and orientation data indicative of the position and theorientation (θ6(t2),d6(t2)) associated to the sixth wood product 12 f atthe second moment in time t2.

For now, the optimization data associated to each of the fourth, fifthand sixth wood products 12 d, 12 e, 12 f are still unknown.

At this stage, referring back to FIG. 2, the method 100 has a step 108of tracking each wood product from the first sample at the first momentin time t1 to the second sample at the second moment in time t2 byassociating the optimization data of each wood product of the firstsample to a respective wood product of the second sample based on theanticipated and actual position and orientation data (θ′(t2),d′(t2)) and(θ(t2),d(t2)).

Indeed, in an exemplary embodiment, the method 100 can have a step ofcalculating a distance parameter between all combinations of theanticipated and actual position and orientation data such that the stepof associating is based on the calculated distance parameters.

The calculus of the distance parameter can vary from an embodiment toanother. For instance, the following matrix shows exemplary distanceparameters associated to each of all combinations between theanticipated and actual position and orientation data of the first andsecond samples 60 and 64 of FIGS. 3A and 4A:

(θ′1(t2), d′1(t2)) (θ′2(t2), d′2(t2)) (θ′3(t2), d′3(t2)) (θ4(t2),d4(t2)) 29 189 353 (θ5(t2), d5(t2)) 166 34 168 (θ6(t2), d6(t2)) 287 14357

In one embodiment, the step of tracking can be performed by associatingeach combination characterized by a calculated distance parametersmaller than a distance parameter threshold.

In this case, assuming that the distance parameter threshold is 142, thecombinations (θ′1(t2),d′1(t2))-(θ′1(t2),d′1(t2)),(θ′2(t2),d′2(t2))-(θ5(t2),d5(t2)) and (θ′3(t2),d′3(t2))-(θ6(t2),d6(t2))are retained, which can be used to associate the first optimization dataof the first wood product to the fourth wood product, to associate thesecond optimization data of the second wood product to the fifth woodproduct and to associate the third optimization data of the third woodproduct to the sixth wood product.

It is contemplated that if an object in the second image remainsunassociated to corresponding optimization data, this object can beconsidered as a new wood product if i) it arrives from an incoming sideof the handling area (e.g., from incoming side 28 a of the handing area28 of FIG. 1); and ii) if new optimization data have been received bythe optimizer. Moreover, if optimization data associated with a givenwood product found in a first image but not found in a second orsubsequent images, these optimization data can be removed from furtherconsideration (e.g., the given wood product can be assumed to be removedfrom the handling area).

In another embodiment, the step of tracking can be performed bydetermining which of the combinations has a minimized distance parameterand associate optimization data of a given wood product of the firstsample associated to the anticipated position and orientation data ofthe determined combination to a given wood product of the second sampleassociated to the actual position and orientation data of the determinedcombination. Once this association is performed, the previouslyassociated wood products can be removed from further consideration sothat this step of associating can be performed iteratively until thereis no longer optimization data remain to associate.

For instance, using the exemplary matrix shown above, the combinationwhich yields a minimized distance parameter is the combination(θ′2(t2),d′2(t2))-(θ5(t2),d5(t2)). In this case, the optimization dataof the second wood product are associated to the fifth wood product andthe second and fifth product are removed from further consideration.

Following removal from consideration the combinations involving thesecond wood product and the fifth wood product, the matrix becomes:

(θ′1(t2), d′1(t2)) (θ′3(t2), d′3(t2)) (θ4(t2), d4(t2)) 29 353 (θ6(t2),d6(t2)) 287 57

Now, the combination which yields a minimized distance parameter is thecombination (θ′3(t2),d′3(t2))-(θ6(t2),d6(t2)). In this case, theoptimization data of the third wood product are associated to the sixthwood product.

Following removal from consideration the combinations involving thethird wood product and the sixth wood product, there only remains theoptimization data associated to the first wood product to associate, andthere only remains the fourth wood product to which it can beassociated. Therefore, the optimization data associated to the firstwood product are associated to the fourth wood product.

By so tracking the optimization data relative to its associated woodproduct across successive ones of a plurality of images representing thehandling area, the processor of the wood tracking system can transmitthe optimization data that corresponds to the wood product that is to betrimmed by the trimmer.

For instance, as it can be seen in FIG. 5, seventh, eighth, and ninthwood products 12 g, 12 h, 12 i of a third sample 70 are shown at a thirdmoment in time t3. A third image 72 representing the third sample 70 ispresented in FIG. 5A. However, by repeatedly performing the steps of themethod 100 described with reference to FIG. 2 on the third image 72 asshown especially in FIG. 5A, these wood products 12 g, 12 h, 12 i can beassociated respectively to the first, second and third wood products 12a, 12 b, 12 c.

Indeed, the first and second wood products 12 a, 12 b have beenreordered along the transverse path between the second moment in time t2and the third moment in time t3.

In this case, the processor can transmit the optimization dataassociated to the second wood product to the trimmer, then theoptimization data associated to the first wood product and then theoptimization data associated to the third wood product.

For the wood tracking system to work in a satisfactory manner, therepetition rate of these steps can be above a given threshold. Theincremental period of time Δt between the first, second and third images62, 66 and 72 is about a fraction of a second. In another embodiment,the incremental period of time Δt between two successive repetition ofthe method is at least 0.05 s (i.e. 20 fps).

As it will be understood, there are various ways of modeling each woodproduct in an image. The following presents one exemplary method ofdoing so.

The step of comparing can includes a step of convoluting the image witha convolution matrix (e.g., [+1|−1]) to obtain a convoluted image.

The step of modeling can include a step of thresholding the image (e.g.,the convoluted image) to obtain a binary image.

The step of modeling can include a step of applying a Hough transform tothe binary image, wherein the position and orientation data and thedistance parameters are determined from a parameter space of the Houghtransform. An example of a Hough transform is presented in U.S. Pat. No.3,069,654, the contents of which are incorporated by reference herein.

Referring back to FIG. 1, the wood tracking system 10 has a lightingsystem 80 for lighting the handling area 28 during use of the woodtracking system 10. As shown in the illustrated example, the lightingsystem 80 is controllable by the processor 42 to provide a controlledlighting environment to the handling area 28. For instance, theprocessor 42 can transmit a control signal to the lighting system 80 inorder to modify the lighting of the handling area 28 based on the images48 acquired from the camera 40. However, the lighting system 80 of thewood tracking system 10 is optional. Indeed, in some embodiments, thehandling area 28 is illuminated by a conventional lighting system of afacility in which the wood tracking system 10 is used. In some otherembodiments, natural illumination (e.g., sunlight) of the handling area28 may be sufficient to allow the camera 40 to generate satisfactoryimages in at least some cases. The camera 40 can have a sensibilitywhich compensates for a poor illumination of the handling area 28.

It is envisaged that the wood tracking system 10 can include a displayscreen 82 in communication with the processor 42 and located a positionalong the production line 11. The display screen 82 can be used todisplay the acquired images 48 in the form of a real-time video and alsooptionally to display optimization data 34 for each wood product 12 suchas to allow validation of the optimization data 34 by a skilledoperator. This can allow to reduce time associated with a validationprocedure of the optimization data to ensure that the optimizer 14 worksin a satisfactory manner in the production line 11. For instance, it maybe possible to validate the optimization data of 20 wood products inless than 5 minutes.

In an embodiment, the optimization data associated to a given one of thewood products are displayed on the display screen 82 when the woodtracking system 10 determines, in an image, that a skilled operator ispointing or touching the given wood product in the handling area 28.

As can be understood, the examples described above and illustrated areintended to be exemplary only. In an embodiment, the trimmer can beprovided in the form of an edger. Moreover, in another embodiment, theconveyor associated with the optimizer can be a transversal conveyor. Insuch an embodiment, the wood products may be tied to one another as theypass under the optimizer and then be freed from one another prior toarrival in the handling area. The scope is indicated by the appendedclaims.

What is claimed is:
 1. A wood tracking system for a production line, thewood tracking system comprising: a wood product optimizer positionedalong a production line; a wood product trimmer positioned downstreamfrom the wood product optimizer in the production line; a conveyorconfigured for moving a plurality of wood products from the wood productoptimizer to the wood product trimmer and across a handling area betweenthe wood product optimizer and the wood product trimmer, the woodproduct optimizer being configured to scan each of the wood products ina given order and to generate optimization data for each wood product;and a computer vision system positioned proximate the handling areaalong the production line, the computer vision system having a camera, aprocessor in communication with the wood product optimizer and with thewood product trimmer and a computer-readable memory for storing theoptimization data, the processor being configured to acquire at leasttwo images from the camera and representing the handling area at atleast two different moments in time, the processor being configured toassociate the optimization data of a given wood product represented in afirst one of the at least two images to a corresponding wood productrepresented in a second one of the at least two images until the givenwood product arrives at the trimmer.
 2. The wood tracking system ofclaim 1 wherein the computer-readable memory having stored thereoninstructions that, when executed by the processor, perform the steps of:determining position and orientation data associated to each woodproduct represented in each of the at least two images; associating theoptimization data of each wood product represented in the first image toa respective wood product represented in the second image based on theposition and orientation data determined in the first and second images.3. The wood tracking system of claim 1 further comprising a lightingsystem in communication with the processor to control a lightingenvironment of the handling area.
 4. The wood tracking system of claim 1wherein the camera includes more than one cameras each having acorresponding field of view associated to a given sub portion of thehandling area.
 5. The wood tracking system of claim 1 wherein the camerahas a frame rate of at least 20 fps.
 6. The wood tracking system ofclaim 1 wherein the camera has a resolution of at least 1 megapixel. 7.A method of tracking wood products being transversely moved across ahandling area of a production line at a transverse speed, the methodcomprising: obtaining position and orientation data and optimizationdata associated to each wood product of a first sample present in thehandling area at a first moment in time; using a processor, anticipatingposition and orientation data of each wood product of the first sampleat a second moment in time assuming an incremental transverse movementbased on the transverse speed and on the position and orientation dataassociated to each wood product of the first sample; acquiring, from acamera, an image representing each wood product of a second samplepresent in at least the handling area at the second moment in time andanalyzing the image to determine actual position and orientation dataassociated to each wood product of the second sample; and tracking eachwood product from the first sample to the second sample by associatingthe optimization data of each wood product of the first sample to arespective wood product of the second sample based on the anticipatedand actual position and orientation data.
 8. The method of claim 7further comprising calculating a distance parameter between allcombinations of the anticipated and actual position and orientation dataand wherein said associating is further based on the calculated distanceparameters.
 9. The method of claim 8 wherein said associating isperformed for each combination characterized by a calculated distanceparameter smaller than a distance parameter threshold.
 10. The method ofclaim 8 wherein said associating includes determining which of thecombinations has a minimized distance parameter and associating a givenwood product of the first sample associated to the anticipated positionand orientation data of the determined combination to a given woodproduct of the second sample associated to the actual position andorientation data of the determined combination.
 11. The method of claim7 wherein the image is a second image and wherein said obtainingincludes acquiring, from the camera, a first image representing eachwood product of the first sample present in the handling area at thefirst moment in time; and analyzing the first image to determine theposition and orientation data associated to each wood product of thefirst sample.
 12. The method of claim 7 wherein said analyzing includesmodeling each wood product in the image as a line having a referencepoint at a given position and extending along a given orientation. 13.The method of claim 12 wherein said modeling includes convoluting theimage with a convolution matrix to obtain a convoluted image.
 14. Themethod of claim 13 wherein said modeling further includes thresholdingthe convoluted image to obtain a binary image.
 15. The method of claim14 wherein said modeling further includes applying a Hough transform tothe binary image and wherein the position and orientation data and thedistance parameters are determined from a parameter space of the Houghtransform.
 16. The method of claim 7 further comprising repeatedlyperforming said anticipating, acquiring and tracking for another imagerepresenting a third sample of elongated wood product at a third momentin time.
 17. The method of claim 16 wherein said repeating is performedat a frame rate of at least 20 fps.
 18. The method of claim 7 furthercomprising storing the position and orientation data on acomputer-readable memory in communication with the processor.
 19. Themethod of claim 7 wherein the incremental movement at the transversespeed is assumed to last for an incremental period of time, the secondmoment in time exceeding the first moment in time by the incrementalperiod of time.
 20. The method of claim 7 further comprising displayingthe optimization data associated with a given wood product on a displayscreen upon determining that an operator points towards or touches thegiven wood product in at least one of the first and the second images.